ModelDB is moving. Check out our new site at The corresponding page is

Robust transmission in the inhibitory Purkinje Cell to Cerebellar Nuclei pathway (Abbasi et al 2017)

 Download zip file 
Help downloading and running models

1 . Abbasi S, Hudson AE, Maran SK, Cao Y, Abbasi A, Heck DH, Jaeger D (2017) Robust Transmission of Rate Coding in the Inhibitory Purkinje Cell to Cerebellar Nuclei Pathway in Awake Mice PLOS Computational Biology
2 . Steuber V, Schultheiss NW, Silver RA, De Schutter E, Jaeger D (2011) Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells. J Comput Neurosci 30:633-58 [PubMed]
3 . Steuber V, Jaeger D (2013) Modeling the generation of output by the cerebellar nuclei. Neural Netw 47:112-9 [PubMed]
4 . Steuber V, De Schutter E, Jaeger D (2004) Passive models of neurons in the deep cerebellar nuclei: the effect of reconstruction errors Neurocomputing 58-60:563-568
5 . Luthman J, Hoebeek FE, Maex R, Davey N, Adams R, De Zeeuw CI, Steuber V (2011) STD-dependent and independent encoding of input irregularity as spike rate in a computational model of a cerebellar nucleus neuron. Cerebellum 10:667-82 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum deep nucleus neuron;
Channel(s): I h; I T low threshold; I L high threshold; I Na,p; I Na,t; I K,Ca; I K;
Gap Junctions:
Receptor(s): AMPA; NMDA; GabaA;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: GENESIS;
Model Concept(s): Synaptic Integration;
Implementer(s): Jaeger, Dieter [djaeger at];
Search NeuronDB for information about:  GabaA; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I K; I h; I K,Ca; Gaba; Glutamate;
function [f,findx]=getfgrid(Fs,nfft,fpass)
% Helper function that gets the frequency grid associated with a given fft based computation
% Called by spectral estimation routines to generate the frequency axes 
% Usage: [f,findx]=getfgrid(Fs,nfft,fpass)
% Inputs:
% Fs        (sampling frequency associated with the data)-required
% nfft      (number of points in fft)-required
% fpass     (band of frequencies at which the fft is being calculated [fmin fmax] in Hz)-required
% Outputs:
% f         (frequencies)
% findx     (index of the frequencies in the full frequency grid). e.g.: If
% Fs=1000, and nfft=1048, an fft calculation generates 512 frequencies
% between 0 and 500 (i.e. Fs/2) Hz. Now if fpass=[0 100], findx will
% contain the indices in the frequency grid corresponding to frequencies <
% 100 Hz. In the case fpass=[0 500], findx=[1 512].
if nargin < 3; error('Need all arguments'); end;
f=0:df:Fs; % all possible frequencies
if length(fpass)~=1;
   findx=find(f>=fpass(1) & f<=fpass(end));
   clear fmin

Loading data, please wait...